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• W2134155890 abstract "A variety of techniques currently exist for measuring the similarity between time series datasets. Of these techniques, the methods whose matching criteria is bounded by a specified ε threshold value, such as the LCSS and the EDR techniques, have been shown to be robust in the presence of noise, time shifts, and data scaling. Our work proposes a new algorithm, called the Fast Time Series Evaluation (FTSE) method, which can be used to evaluate such threshold value techniques, including LCSS and EDR. Using FTSE, we show that these techniques can be evaluated faster than using either traditional dynamic programming or even warp-restricting methods such as the Sakoe-Chiba band and the Itakura Parallelogram." @default.
• W2134155890 created "2016-06-24" @default.
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• W2134155890 date "2007-06-11" @default.
• W2134155890 modified "2023-10-02" @default.
• W2134155890 title "An efficient and accurate method for evaluating time series similarity" @default.
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• W2134155890 doi "https://doi.org/10.1145/1247480.1247544" @default.
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